Multidimensional Particle Analysis Data Cluster Reconstruction

1. A method for reconstructing multidimensional particle analysis data clusters on a computing device, the multidimensional particle analysis data including data for each particle for at least three dimensions, comprising: obtaining, on the computing device, a set of segmented two-dimensional projections corresponding to multidimensional particle analysis data associated with a biological sample of particles, each segmented two-dimensional projection in the set being a projection of the same multidimensional particle analysis data as the other two-dimensional projections in the set, each segmented two-dimensional projection in the set being a projection on two dimensions that are a different pair of dimensions than any of the other two-dimensional projections in the set, each segmented two-dimensional projection having a segmentation which divides the data in the two-dimensional projection into one or more two-dimensional clusters each associated with corresponding particle populations in the biological sample; and reconstructing, on the computing device, a segmentation of the particle analysis data into one or more multidimensional clusters based on the two-dimensional clusters in at least two different projections in the set of segmented two-dimensional projections, the one or more multidimensional clusters being defined in at least three dimensions.

2. The method of claim 1 , wherein the obtaining the set of segmented two-dimensional projections comprises obtaining two or more segmented two-dimensional projections, each segmented two-dimensional projection sharing a single dimension, and only a single dimension, with another segmented two-dimensional projection in the set.

3. The method of claim 2 , wherein the dimensions represent measured physical property values of particles.

4. The method of claim 2 , wherein the reconstructing one or more multidimensional clusters comprises the following steps implemented on the computing device: selecting a data point in the multidimensional particle analysis data; determining, for each segmented two-dimensional projection, a respective two-dimensional point corresponding to the selected data point; identifying two-dimensional clusters containing the determined two-dimensional points in the two-dimensional projections; and associating the selected data point with a multidimensional cluster based on the identified two-dimensional clusters.

5. The method of claim 4 , wherein the associating the selected data point with a multidimensional cluster comprises associating the selected data point with a multidimensional cluster containing data points corresponding to the same two-dimensional cluster identification.

6. The method of claim 4 , wherein the selecting a data point comprises selecting a data point having a value above a threshold.

7. The method of claim 1 , wherein the obtaining a set of segmented two-dimensional projections corresponding to multidimensional particle analysis data comprises obtaining a set of segmented two-dimensional projections corresponding to particle analysis data including measurements of at least three parameters selected from the following group of parameters: direct current, volume, radio frequency, opacity, one or more types of light scatter, axial light loss, and fluorescence.

8. The method of claim 1 , wherein the obtaining a set of segmented two-dimensional projections corresponding to multidimensional particle analysis data comprises obtaining a set of segmented two-dimensional histograms corresponding to the multidimensional particle analysis data.

9. The method of claim 1 , wherein the obtaining a set of segmented two-dimensional projections corresponding to multidimensional particle analysis data comprises obtaining a set of segmented two-dimensional scattergrams corresponding to the multidimensional particle analysis data.

10. The method of claim 1 , further comprising displaying the reconstructed multidimensional clusters on a display.

11. The method of claim 1 , further comprising storing the reconstructed multidimensional clusters on a storage device.

12. The method of claim 1 , further comprising counting particles in each of the reconstructed multidimensional clusters.

13. The method of claim 1 , further comprising: identifying cross-relations between two-dimensional clusters in at least two different two-dimensional projections, wherein the reconstructing the one or more multidimensional clusters is based on the identified cross-relations between the two-dimensional clusters.

14. The method of claim 13 , using the cross-relations to identify clusters in different two-dimensional projections that correspond to the same particle populations in the biological sample.

15. The method of claim 13 , further comprising: using the cross relations to identify a particle population in a two-dimensional projection to identify a population of particles in a two-dimensional projection that was not identified by two-dimensional clustering the data in the two-dimensional projection without the cross relations.

16. A computer-implemented system for reconstructing multidimensional particle analysis data clusters, the multidimensional particle analysis data including data for each particle for at least three dimensions, comprising on at least one computing device: a two-dimensional segmentation module that obtains a set of two-dimensional projections of multidimensional particle analysis data associated with a biological sample of particles, each two-dimensional projection in the set being a projection of the same multidimensional particle analysis data as the other two-dimensional projections in the set, each two-dimensional projection in the set being a projection on two dimensions that are a different pair of dimensions than any of the other two-dimensional projections in the set, and segments each of the two-dimensional projections into one or more two-dimensional clusters, wherein each two-dimensional cluster corresponds to a particle population in the biological sample; a two-dimensional cluster classification module that, for each multidimensional data point in the multidimensional particle analysis data that has a value above a pre-specified threshold, identifies two-dimensional clusters in the two-dimensional projections that contain the multidimensional data point; and a multidimensional cluster reconstruction module that groups multidimensional data points based on the identified two-dimensional clusters in at least two different projections in the set of two-dimensional projections to reconstruct one or more multidimensional clusters, where the multidimensional clusters are defined in at least three different dimensions.

17. The system of claim 16 , further comprising a hematology analyzer that interrogates particles in a biological sample to obtain the multidimensional particle analysis data, and outputs the multidimensional particle analysis data to the two-dimensional segmentation module.

18. The system of claim 16 , wherein the two-dimensional projections are two-dimensional histograms.

19. The system of claim 16 , wherein the two-dimensional projections are two-dimensional scattergrams.

20. The method of claim 16 , wherein the dimensions represent measured physical property values of particles.

21. A method for reconstructing multidimensional particle analysis data clusters, comprising: (a) passing particles from a biological sample through a measuring region of a particle analyzer; (b) interrogating each particle passing through the measuring region with at least three parameters; (c) detecting the at least three parameters with one or more detectors; (d) storing the detected at least three parameters as multidimensional particle analysis data having at least three dimensions, each dimension corresponding to one of the detected parameters; (e) generating a set of two-dimensional projections corresponding to the multidimensional particle analysis data, each two-dimensional projection in the set being a projection of the same multidimensional particle analysis data as the other two-dimensional projections in the set, each two-dimensional projection in the set having a different pair of dimensions than the other two-dimensional projections in the set; (f) segmenting the two-dimensional projections in the set into two-dimensional clusters associated with particle populations in the biological sample; and (g) reconstructing a segmentation of the particle analysis data into one or more multidimensional clusters based on the segmented two-dimensional clusters in at least two different two-dimensional projections in the set of two-dimensional projections, where the multidimensional clusters are defined in at least three different dimensions.

22. The method of claim 21 , further comprising displaying the reconstructed multidimensional clusters on a display.

23. The method of claim 21 , further comprising storing the reconstructed multidimensional clusters on a storage device.

24. The method of claim 21 , further comprising counting particles in each of the reconstructed multidimensional clusters.

25. The method of claim 21 , wherein the at least three parameters comprises at least three parameters selected from the following group of parameters: direct current, volume, radio frequency, opacity, one or more types of light scatter, axial light loss, and fluorescence.

26. The method of claim 21 , further comprising: identifying cross-relations between two-dimensional clusters in at least two different two-dimensional projections, wherein the reconstructing the one or more multidimensional clusters is based on the identified cross-relations between the two-dimensional clusters.

27. The method of claim 26 , using the cross-relations to identify clusters in different two-dimensional projections that correspond to the same particle populations in the biological sample.

28. The method of claim 26 , further comprising: using the cross relations to identify a particle population in a two-dimensional projection to identify a population of particles in a two-dimensional projection that was not identified by two-dimensional clustering the data in the two-dimensional projection without the cross relations.

29. A system for reconstructing multidimensional particle analysis data clusters, comprising: a particle analyzer that includes: a preparation system for preparing a biological sample containing a plurality of particles for analysis; a transducer module having a measuring region, a plurality of interrogation sources to interrogate at least one of the particles passing through the measuring region, and at least one detector to detect a plurality of parameters associated with at least one of the particles; and a memory that stores the detected parameters as multidimensional particle analysis data, the multidimensional particle analysis data having at least three dimensions, each dimension corresponding to one of the detected parameters; a two-dimensional cluster classification module that receives a set of two-dimensional projections of the multidimensional particle analysis data, each two-dimensional projection in the set being a projection of the same multidimensional particle analysis data as the other two-dimensional projections in the set, each two-dimensional projection in the set having a different pair of dimensions than the other projections in the set, and for each multidimensional data point in the multidimensional particle analysis data that has a value above a pre-specified threshold, identifies two-dimensional clusters in the two-dimensional projections that contain the multidimensional data point; a two-dimensional segmentation module that segments the two-dimensional projections into two-dimensional clusters, wherein each two-dimensional cluster corresponds to a particle population in the biological sample; and a multidimensional cluster reconstruction module that groups multidimensional data points based on the identified two-dimensional clusters in at least two different two-dimensional projections in the set of two-dimensional projections to reconstruct one or more multidimensional clusters, the multidimensional clusters being defined in at least three dimensions.

30. The system of claim 29 , wherein the multidimensional cluster reconstruction module is further configured to identify a population of particles in one of the two-dimensional projections that was not identified by segmenting the data in the one of two-dimensional projections into two-dimensional clusters.